Bart Keyword Extractor

🚀 bart_keywords模型

该模型基于facebook/bart-large进行微调，可从文本中提取主要关键词，能有效解决文本信息提取难题，为文本处理提供高效准确的关键词提取方案。

🚀 快速开始

此模型是 facebook/bart-large 在名为 sunhaozhepy/ag_news_keywords_embeddings 的数据集上微调后的版本，用于从文本中提取主要关键词。 它在评估集上取得了以下结果：

• 损失值：0.6179

代码示例

from transformers import pipeline

pipe = pipeline('summarization', model='bart_keywords_model')
print(pipe("Aria Opera GPT version - All the browsers come with their own version of AI. So I gave it a try and ask it with LLM it was using. First if all it didn't understand the question. Then I explained and asked which version. I got the usual answer about a language model that is not aware of it's own model I find that curious, but also not transparent. My laptop, software all state their versions and critical information. But something that can easily fool a lot of people doesn't. What I also wonder if the general public will be stuck to ChatGPT 3.5 for ever while better models are behind expensive paywalls."))

✨ 主要特性

• 基于facebook/bart-large微调，具备强大的文本理解能力。
• 能够准确从文本中提取主要关键词。

📚 详细文档

训练超参数

训练过程中使用了以下超参数：

• 学习率：5e-05
• 训练批次大小：8
• 评估批次大小：8
• 随机种子：42
• 梯度累积步数：16
• 总训练批次大小：128
• 优化器：Adam（β1 = 0.9，β2 = 0.999，ε = 1e-08）
• 学习率调度器类型：线性
• 学习率调度器热身步数：500
• 训练轮数：3

训练结果

框架版本

• Transformers 4.35.2
• Pytorch 2.1.0+cu118
• Datasets 2.15.0
• Tokenizers 0.15.0

📄 许可证

本模型采用 Apache-2.0 许可证。